Publications related to Laplacian Operator, Diffusion Flow and Active Contour on non-Euclidean Images

Buckling of pressurized spherical shells containing a through-thickness defect

Pedro Miguel Nunes Pereira de Almeida Reis, Matteo Pezzulla, Dong Yan

We present a study on the pressure buckling of thin, elastic spherical shells containing a thickness defect. Methodologically, we combine precision model experiments, finite element simulations, and a reduced axisymmetric shell model. We observe qualitativ ...

PERGAMON-ELSEVIER SCIENCE LTD2020

Coordinate Difference Matrices

Martin Vetterli, Gilles Baechler, Miranda Krekovic, Golnooshsadat Elhami

In many problems such as phase retrieval, molecular biology, source localization, and sensor array calibration, one can measure vector differences between pairs of points and attempt to recover the position of these points; this class of problems is called ...

SIAM PUBLICATIONS2020

UCLID-Net: Single View Reconstruction in Object Space

Pascal Fua, Benoît Alain René Guillard, Edoardo Remelli

Most state-of-the-art deep geometric learning single-view reconstruction approaches rely on encoder-decoder architectures that output either shape parametrizations or implicit representations. However, these representations rarely preserve the Euclidean st ...

2020

Fully 3D Printed Mechanical Pressure Sensors: A Comparison of Sensing Mechanisms

Danick Briand, Ryan Mitchell van Dommelen, Rubaiyet Iftekharul Haque, Julien Gaëtan Berger

Recent advances in 3D printing techniques are allowing for new ways to manufacture sensors with materials and geometries previously not exploited. In this work we present a fabrication approach for fully 3D printed soft mechanical pressure sensors, as well ...

IEEE2020

Bayesian Optimization Meets Riemannian Manifolds in Robot Learning

Sylvain Calinon, Noémie Laure Gwendoline Jaquier

Bayesian optimization (BO) recently became popular in robotics to optimize control parameters and parametric policies in direct reinforcement learning due to its data efficiency and gradient-free approach. However, its performance may be seriously compromi ...

2019

Escaping from saddle points on Riemannian manifolds

Nicolas Henri Bernard Flammarion, Yue Sun

We consider minimizing a nonconvex, smooth function f on a Riemannian manifold M. We show that a perturbed version of Riemannian gradient descent algorithm converges to a second-order stationary point (and hence is able to escape saddle points on the manif ...

2019

Improved Bounds for Discretization of Langevin Diffusions: Near-Optimal Rates without Convexity

Nicolas Henri Bernard Flammarion

We consider minimizing a nonconvex, smooth function

f

on a Riemannian manifold

\mathcal{M}

. We show that a perturbed version of Riemannian gradient descent algorithm converges to a second-order stationary point (and hence is able to escape saddle point ...

2019

Reparameterizing Discontinuous Integrands for Differentiable Rendering

Wenzel Alban Jakob, Guillaume Rémi Bruno Loubet

Differentiable rendering has recently opened the door to a number of challenging inverse problems involving photorealistic images, such as computational material design and scattering-aware reconstruction of geometry and materials from photographs. Differe ...

ASSOC COMPUTING MACHINERY2019

A Gauss-Bonnet Theorem for Asymptotically Conical Manifolds and Manifolds with Conical Singularities

Adrien Giuliano Marcone

The purpose of this thesis is to provide an intrinsic proof of a Gauss-Bonnet-Chern formula for complete Riemannian manifolds with finitely many conical singularities and asymptotically conical ends. A geometric invariant is associated to the link of both ...

EPFL2019

Engineered nanostructures' characterization by spectral interferometric microscopy

Toralf Scharf, Michail Symeonidis

We characterize engineered nanostructures with sizes smaller than half a wavelength using spectrally resolved interferometry. We analyze the response of the meta-atom of interest, which has a raspberry-like geometry. To identify the origin of the response, ...

SPIE-INT SOC OPTICAL ENGINEERING2019

Laplacian Operator, Diffusion Flow and Active Contour on non-Euclidean Images

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Buckling of pressurized spherical shells containing a through-thickness defect

Coordinate Difference Matrices

UCLID-Net: Single View Reconstruction in Object Space

Fully 3D Printed Mechanical Pressure Sensors: A Comparison of Sensing Mechanisms

Bayesian Optimization Meets Riemannian Manifolds in Robot Learning

Escaping from saddle points on Riemannian manifolds

Improved Bounds for Discretization of Langevin Diffusions: Near-Optimal Rates without Convexity

Reparameterizing Discontinuous Integrands for Differentiable Rendering

A Gauss-Bonnet Theorem for Asymptotically Conical Manifolds and Manifolds with Conical Singularities

Engineered nanostructures' characterization by spectral interferometric microscopy

Buckling of pressurized spherical shells containing a through-thickness defect

A Gauss-Bonnet Theorem for Asymptotically Conical Manifolds and Manifolds with Conical Singularities

Engineered nanostructures' characterization by spectral interferometric microscopy

Fully 3D Printed Mechanical Pressure Sensors: A Comparison of Sensing Mechanisms

Coordinate Difference Matrices

Escaping from saddle points on Riemannian manifolds

Bayesian Optimization Meets Riemannian Manifolds in Robot Learning

UCLID-Net: Single View Reconstruction in Object Space

Reparameterizing Discontinuous Integrands for Differentiable Rendering

Improved Bounds for Discretization of Langevin Diffusions: Near-Optimal Rates without Convexity